Developing an innovative region-wide risk-informed earthquake early warning decision support system

Abstract

Earthquake early warning (EEW) systems provide brief notice to targeted audiences (e.g., civil protection services) of potentially destructive seismic events. This short warning time can be used to take rapid but effective actions for reducing impending earthquake-related losses (e.g., shutting off gas supplies to prevent fires, evacuating the ground floors of buildings to mitigate casualties). Current EEW systems in use around the world do not employ risk-based metrics to support decision making for alert triggering by various end users. Instead, thresholds for issuing EEW alarms are typically based on seismological parameters (e.g., magnitude, ground-shaking intensity value) without regard for the possible consequences of triggering or not the warning. Some recent research efforts have focused on developing risk-informed EEW decision-making methodologies, but these have been limited to applications involving single assets (e.g., buildings) or specific infrastructure systems, and are not suitable for region-wide EEW. This paper addresses the limitations of state-of-the-art in EEW decision making by developing an end-user-, risk-oriented EEW decision support system (EEW DSS) for a building portfolio. The proposed EEW DSS combines conventional seismic risk assessment tools with a multi-criteria decision algorithm that relies on stakeholder risk preference input, and explicitly integrates necessary considerations associated with a region-wide, heterogenous set of buildings (e.g., spatially correlated ground motions, varying impacts of triggering or not the alarm for different building occupancies, etc.). The EEW DSS is tested for a series of earthquakes across a hypothetical urban system (>4,000 buildings). We find that the risk-informed magnitude threshold for alarm issuance increases with distance (as expected), and that the optimal action for a given magnitude/distance may depend on stakeholder risk preferences (consistent with previous studies). The proposed methodology has the potential to convert region-wide EEW systems into powerful people-centered loss-mitigation tools.